metadata
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electra-finetuned-ner-copious
results: []
electra-finetuned-ner-copious
This model is a fine-tuned version of google/electra-base-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0614
- Precision: 0.7361
- Recall: 0.7681
- F1: 0.7518
- Accuracy: 0.9814
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 63 | 0.0999 | 0.4927 | 0.4870 | 0.4898 | 0.9675 |
| No log | 2.0 | 126 | 0.0677 | 0.6728 | 0.7420 | 0.7057 | 0.9783 |
| No log | 3.0 | 189 | 0.0648 | 0.7153 | 0.7101 | 0.7127 | 0.9795 |
| No log | 4.0 | 252 | 0.0619 | 0.7299 | 0.7638 | 0.7465 | 0.9809 |
| No log | 5.0 | 315 | 0.0614 | 0.7361 | 0.7681 | 0.7518 | 0.9814 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3